Transcript Determination Method
a transcript and determination method technology, applied in the field of transcript determination methods, can solve problems such as large number of parameters, and achieve the effect of accurate assessment of transcript abundan
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example 1
Introduction to NGS Methods
[0091]In order to infer which mRNA molecules were present in the original sample, NGS reads are mapped onto a reference genome with known methods, such as the Burrows-Wheeler transform. For each read this gives a set of genetic coordinates, potentially including information about splice sites. The mapping process is visualized in FIG. 1. Here the location of the short read that has been produced by the sequencer is identified within the reference genome. This process is repeated for all the reads generated by the sequencer, which results in a large number of short sequences on the genetic axis as indicated by the short straight lines below the filled black curve in FIG. 1. The combined statistics of the mapped reads lead to different types of histograms on the genetic axis (i.e. different types of coverage envelope curves). The black filled curve in FIG. 1, for instance, depicts the coverage (envelope). At a given position on the genetic axis the value of ...
example 2
Coordinate Transformations
2.1. Positions in Genome and Transcript Coordinates
[0099]The genetic axis is the sequence of base pairs that have been sequenced for an organism, which usually starts at zero or one and can reach up to several hundred million base pairs long, depending on the complexity of the organism. In addition, the genetic axis is usually subdivided into chromosomes or contigs. The genetic axis is visualized at the top of FIG. 5 which indicates that this graphic represents a selection of a genome on chromosome 11 approximately between base pair 53,242,500 and 53,244,200. A transcript is usually defined as a sequence of exons (exon1, . . . , exonN) on the genetic axis, where the i-th exon is an interval [s(exoni), . . . , e(exoni)] on the genetic axis which starts at s (exoni) and ends at e(exoni). The gap between two successive exons [e(exoni)+1,s(exoni+1)−1] is called an intron and the connection from the last nucleotide preceding an intron to the first nucleotide fol...
example 3
Estimation of Transcript Probabilities and Transcript Specific Probability Distributions
[0109]The model that is described in the following uses mixtures of mixtures of functions and will therefore be called the Mix2 model.
3.1 Mathematical Foundations of the Mix2 Model
[0110]In the following, r can represent both a fragment and a position. However, for convenience, r will always be referred to as a fragment. The probability of observing a particular fragment r in the genetic locus ptotal(r) is a sum of the probabilities of observing the fragment for a transcript weighted by the probability that the transcript generates a fragment. Hence the ptotal(r) is given by the following mixture of probability distributions.
ptotal(r)=∑i=1Nαip(rt=i)(15)
[0111]As described in section 2, if r is compatible with t=i then p(r|t=i)=trans(T(r)|t=i) and p(r|t=i)=0 otherwise. The method assumes that the probability distributions ptrans(r|t=i) are mixtures, i.e.
ptrans(rt=i)=∑j=1Miβi,jptrans(rt=i,b=j)(16)
[01...
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